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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multi-agent Reinforcement Learning in Sequential Social Dilemmas · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1702.03037/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1702.03037/feed.xml" rel="self" type="application/rss+xml" /><item><title>Multi-agent Reinforcement Learning in Sequential Social Dilemmas — mentioned by hcheemskerk</title><link>https://news.ycombinator.com/item?id=20129867</link><guid isPermaLink="false">urn:hackerpapers:mention:1702.03037:20129867</guid><pubDate>Sat, 08 Jun 2019 00:47:38 GMT</pubDate><description>&lt;p&gt;Sounds like you could adapt Leibo’s sequential social dilemma games. https://arxiv.org/abs/1702.03037 Instead of a total collective reward being the goal, you’d have team-based scores. You’d need cooperation within the team, and aggressive action against the enemy team. Here’s an implementation of 2 games https://github.com/eugenevinitsky/sequential_social_dilemma_...&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1702.03037/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.MA</category></item></channel></rss>
